Description

You will design and implement production-ready AI systems and machine learning workflows.

Responsibilities

• Build, scale, manage, and monitor end-to-end ML pipelines.
• Implement generative AI, agents, and multi-agent collaboration frameworks.
• Deploy AI workloads to production using CI/CD principles and version control.
• Integrate MCP servers into real-world AI implementations.
• Manage distributed computing tasks within containerized environments.

Required Skills

• Minimum 2 years of hands-on AI Engineering experience.
• Proficiency in Python.
• Experience with Kubernetes.
• Strong understanding of Generative AI and agentic workflows.
• Knowledge of multi-agent collaboration and MCP servers.
• Practical application of CI/CD principles for AI workloads.
• Experience with distributed computing.
• Degree in Computer Science or Engineering.

Key Skills

Education

Any Graduate